Hybrid electromagnetic field signal detection system for human bioelectrical signal monitoring

ABSTRACT

The present disclosure includes an electromagnetic field detection and monitoring system. The system includes passive detection, active detection, and signal processing capabilities. At least one embodiment includes a body worn system with sensing, processing, communications, and data storage capabilities. The system provides wearable antennas to transfer the EMF energy in its electrical or magnetic forms into the sensor efficiently. A specially designed processing algorithm can process the collected data and generated the results for medical professionals to read and make decisions.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationSer. No. 62/482,123, filed on Apr. 5, 2017, the entire contents of whichare hereby incorporated by reference.

GOVERNMENT LICENSE RIGHTS

Some embodiments of the invention were made with government supportunder W81XWH-17-C-0133 awarded by the U.S. Army Medical Research andMateriel Command. The government has certain rights in the invention.

TECHNICAL FIELD

The present disclosure is directed generally to electromagnetic fielddetection and monitoring system, and more specifically, to monitor asoldier or field operator's health condition based on electromagneticsfield (EMF) signals emitted from the human body.

BACKGROUND

In a dynamic, fast changing environment, and especially a hostile onesuch as a warzone, it is preferable to be able to accurately, timely,and reliably monitor the health condition of a field operator.

The EMF signals from the human body are emitted at two extreme ends ofthe electromagnetic spectrum. The two extremes correspond to very low(e.g., KHz to Hz range) and very high (e.g., equal or higher than THz)frequencies on the electromagnetic spectrum. In order to detectbioelectrical signals from the human body, infrared radiation (e.g., THzrange) may be projected on, and electrodes attached to, the skin forobtaining electroencephalogram (EEG) or electrocardiography (ECG)signals.

There are technical difficulties in implementing a health monitoringsystem that is based on monitoring these electromagnetic signals of twoextreme ends and nevertheless suitable for said dynamic, fast changingenvironment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of a passive detection environment in accordancewith one or more embodiments of the present disclosure.

FIG. 2 is a diagram of an active detection environment in accordancewith one or more embodiments of the present disclosure.

FIG. 3 depicts a diagram of an antenna system in accordance with one ormore embodiments of the present disclosure.

FIG. 4 depicts an antenna signal path in accordance with one or moreembodiments of the present disclosure.

FIG. 5 depicts a circuit diagram of antenna circuit in accordance withone or more embodiments of the present disclosure.

FIG. 6 depicts a block diagram of an EMF signal path in accordance withone or more embodiments of the present disclosure.

FIG. 7 depicts a block diagram of an EMF signal path in accordance withone or more embodiments of the present disclosure.

FIG. 8 depicts a block diagram of an EMF signal path in accordance withone or more embodiments of the present disclosure.

FIG. 9 is a high-level block diagram illustrating an example of aprocessing system in which at least some operations described herein canbe implemented, consistent with various embodiments.

FIG. 10 is an active detection environment in accordance with one ormore embodiments of the present disclosure.

FIG. 11 depicts a chart of contact points in accordance with one or moreembodiments of the present disclosure.

DETAILED DESCRIPTION

In order to achieve the goal of detecting the physical conditions of ahuman body in a fast changing and dynamic environment, such as awarzone, there are a number of technical hurdles. First, the wearableantennas should be thin, lightweight, low maintenance, robust,inexpensive and easily integrated in sensing circuits. Second, thesystem should be able to detect a frequency range between the extremelylow frequency (ELF) band to the very low frequency (VLF) band. ELF isdefined by the International Telecommunication Union (ITU) aselectromagnetic radio waves with frequencies from 3 to 30 Hz. VLF isdefined by the International Telecommunication Union (ITU) aselectromagnetic radio waves with frequencies from 3 kHz to 30 kHz.Third, system must be able to exclude uncertainty from weak EMF signals.Fourth, the detected EMF signals must be processed to obtainbioelectrical signals that are useful for health monitoring and medicaldiagnostics. Last but not least, the detection system needs to benon-intrusive so as not to adversely affect the subject's performance,and yet maintains an acceptable level of accuracy. There are additionalchallenges for the selection of textile materials, circuit assembly,manufacturing, and performance reliability.

Traditional EMF signal detection utilizes contact-based electrodes. Theelectrode can be a tiny patch that connects to the patient for sensingbioelectric potential. This electrical activity can be viewed as a smallelectric field or flux of charge-carrying particles (i.e., current). Theelectrodes work as transducers that convert the current flow from thebody into the electron flow of the metallic wire. Often a high ionicconcentration gel is used in the skin-electrode interface to increaseconductivity due to small signal magnitude.

However, such an implementation faces several disadvantages. Forexample, one disadvantage is the time and effort necessary to create aninitial contact between the electrode and the skin. Another disadvantageis that the connection between the electrode and the skin maydeteriorate over time. This may occur when the high ionic concentrationgel dries over time. This may also occur if the electrode is pulled awayfrom the skin. When the contact deteriorates, the quality of the signalfalls drastically. This concern is especially important in a fastchanging and dynamic environment, such as a warzone where theelectrode's contact to the patient's skin deteriorates rapidly.Additionally, the electrode may impede movement of the subject resultingin undesirable and dangerous loss of performance in the environment.

There have been implementations that attempt contact-less EMF detectionby using traditional electrodes and operates by capacitive coupling. Inother words, the electrode that operates by capacitive coupling treatsthe gap between the electrode and the skin as a large capacitor. Such amodel has the drawback that the coupling capacitance decreases rapidlyas the distance between the electrode and the skin increases. Therefore,the electrode may only operate in a limited distance from the skin.Also, it is difficult to discern the locations of the signal sources insuch implementation. These limitations make this model not suitable forEMF detection in a fast changing and dynamic environment.

Traditionally, only contact-based electrodes have been used forbioelectrical signal detection because there are several challenges tonon-contact EMF detection. Antenna-based EEG/ECG signal detection occursat a distance from the skin that is greater than the distance between acontact-based electrode and the skin. The antenna frequency is very low(10 Hz to 10 KHz) and thus its wavelength is long (e.g., the wavelengthof a 5 KHz signal is about 60,000 meters and the wavelength of a 10 Hzsignal is about 30,000,000 meters). Additionally, the minimum requiredelectrical wavelength for the traditional antenna is 0.1 wavelength toguarantee an efficient radiation efficiency. Therefore, antenna-basedEEG/ECG has not been implemented because the large size of the antennawould be cumbersome and dangerous in a fast changing and dynamicenvironment.

Accordingly, introduced here is a technique to measure and track EMFsignals, which is based on a new concept of detecting both contact andnon-contact EMF signals. Additionally, signal processing can beperformed by one or more embodiments for signature extraction and forrejecting interference from EMF signals. More specifically, theembodiments disclosed here can use a single or multiple EMF sensors thatcan be placed at various strategic locations, where the locations canenable the sensors to detect valuable signs of trauma and forecastphysical conditions impacting the human's ability to operate missions inthe field or during training process. The placement of such sensors canbe part of an electro-textile combat and operations uniform. Someembodiments provide a body worn system equipped with sensing,processing, communications, and storage capabilities. The concept of thedisclosed sensing system is to have wearable antennas capable oftransferring the EMF energy in its electrical or magnetic forms into thesensors. The EMF energy is then processed to obtain bioelectricalsignals indicating the physical conditions of the monitored human body.

EMF can be acquired from self-emission (i.e., passive detection) andreflection (i.e., active detection) from the human body. EMFself-emission is a function of numerous components. For example, randomor pseudo noise can be induced by human muscle activities, minorcurrents near brain or heart, and body static excitations.Electromagnetic (EM) reflection is induced by the incoming EM energyfrom an external EM source coupling to the human body then there-emission is excited. Both self and reflected EMF can be measuredusing electrical probes, magnetic loops, and antenna systems with goodreceiver sensitivity at the low end of the EM spectrum. Between twoextremes of EM spectrum, these signals are usually very weak due tono-higher-frequency human energy emission (e.g., muscle pulse).Additionally, most of the non-linear effects in higher frequency arehappening very short in time and narrow in its dynamic range in terms ofamplitude.

Passive measurements may play a critical role in defining the state ofthe biological system. Active measurements on dead systems or selectedorganic chemical solutions along with passive intermodulationmeasurements and signal processing is used to further define thebiological system in detail. ECG/EEG signals vary from the microvolt tothe millivolt range and are the relatively stronger signal in humantissue. Due to this small voltage, the signals measured need to beamplified for better access.

In accordance with some embodiments, biopotential amplifiers may havehigh input impedance and are designed for safety, since excessiveinduced current may produce a significant shock to the living organism.Isolation and protection circuitry limit the any currents through theelectrodes to safe levels. For proper interface to outside circuits, theoutput impedance of the amplifier desirably should be very low, allowingto drive any external loads with a minimal distortion. The amplifiersdesirably should have a high rejection ratio (e.g., in differentialmode) to eliminate large offset signals. Generally speaking, a rejectionratio of 30 db (i.e., 1000 times) may be considered “high.” One of themost factors of EMF detection is the noise level, or noise floor, whichis highest at lower frequencies. Therefore, according to one or moreembodiments, biopotential amplifiers are differential which can minimizenoise from the ground.

Further, in some embodiments, the EMF detection system can performactive harmonic signal calibration in order to understand and calibratethe intermodulation from the mixer, cables, signal generators, anddigitizer. In particular, the system can perform a two-tone measurementaround the frequency range of the interested signals and, in someimplementations, up to the 7th order of its harmonics. For example, thetest starts with two-tone signals feeding into the RF mixer in itsworking frequency range. The frequency mixer may have a low-frequencylocal oscillator (LO) signal, which may be as low as 500 Hz, in someexamples. The system can also feed two tones above 500 Hz and can, forexample, sweep the LO with a 100-Hz step frequency from 5 kHz to 5.5 kHzand keep the input signal at 1000 Hz.

The EMF detection system can also perform vital signal generation bywaveform generator and active measurement. In some examples, the systemgenerates a body signal (e.g., an ECG signal) and then measures thedetected signal. In order to differentiate a normal ECG signal andarrhythmias signal, the system generates three different ECGs. One is anormal ECG signal, and the other two are arrhythmias (e.g., tachycardiaand bradycardia). Each signal contains different features in both thetime and frequency domain (e.g., such as the bandwidth changes). Forexample, tachycardia has a wider bandwidth than the normal ECG, andbradycardia has a narrower bandwidth than the normal one.

Finally, the EMF detection system can perform ECG signal detection atdifferent locations of the body. At each measurement point, ECG may berecorded for 10 seconds at the sampling rate of 1000 samples/second. Alow pass filter is applied to clean the signal. Both the original ECGsignal and filtered signal may be plotted together for comparison.Additionally, the FFT spectrum of each original ECG signal may be usedto analyze the results. Depending on the implementation, the system canalso measure vital signals measured at different body positions. It isobserved that ECG signal typically still dominates the vital signaldetection, but other types of vital signal from the frequency domain,such as a 20 Hz signal around the stomach. This 20 Hz vital signal maybe generated from stomach or intestine activities.

As described in further detail below, the disclosed embodiments here canfurther include a hybrid sensor system and signal processing to capturethe EMF effects and track the EMF signatures in time and time-frequencydomains. Notably, the disclosed system design makes the EMF tractableand repeatable.

In the following, numerous specific details are set forth to provide athorough understanding of the presently disclosed technology. In otherembodiments, the techniques introduced here can be practiced withoutthese specific details. In other instances, well-known features, such asspecific fabrication techniques, are not described in detail in order toavoid unnecessarily obscuring the present disclosure. References in thisdescription to “an embodiment,” “one embodiment,” or the like, mean thata particular feature, structure, material, or characteristic beingdescribed is included in at least one embodiment of the presentdisclosure. Thus, the appearances of such phrases in this specificationdo not necessarily all refer to the same embodiment. On the other hand,such references are not necessarily mutually exclusive either.Furthermore, the particular features, structures, materials, orcharacteristics can be combined in any suitable manner in one or moreembodiments. Also, it is to be understood that the various embodimentsshown in the figures are merely illustrative representations and are notnecessarily drawn to scale.

Several details describing structures or processes that are well-knownand often associated with EMF detection and corresponding systems andsubsystems, but that can unnecessarily obscure some significant aspectsof the disclosed techniques, are not set forth in the followingdescription for purposes of clarity. Moreover, although the followingdisclosure sets forth several embodiments of different aspects of thepresent disclosure, several other embodiments can have differentconfigurations or different components than those described in thissection. Accordingly, the introduced techniques can have otherembodiments with additional elements or without several of the elementsdescribed below.

Many embodiments of the present disclosure described below can take theform of computer- or controller-executable instructions, includingroutines executed by a programmable computer or controller. Thoseskilled in the relevant art will appreciate that the introducedtechniques can be practiced on computer or controller systems other thanthose shown and described below. The techniques introduced herein can beembodied in a special-purpose computer or data processor that isspecifically programmed, configured or constructed to perform one ormore of the computer-executable instructions described below.Accordingly, the terms “computer” and “controller” as generally usedherein refer to any data processor and can include Internet appliancesand handheld devices (including palm-top computers, wearable computers,cellular or mobile phones, multi-processor systems, processor-based orprogrammable consumer electronics, network computers, mini computers andthe like). Information handled by these computers and controllers can bepresented at any suitable display medium, including a liquid crystaldisplay (LCD). Instructions for performing computer- orcontroller-executable tasks can be stored in or on any suitablecomputer-readable medium, including hardware, firmware or a combinationof hardware and firmware. Instructions can be contained in any suitablememory device, including, for example, a flash drive, USB device, and/orother suitable medium.

The terms “coupled” and “connected,” along with their derivatives, canbe used herein to describe structural relationships between components.It should be understood that these terms are not intended as synonymsfor each other. Rather, in particular embodiments, “connected” can beused to indicate that two or more elements are in direct contact witheach other. Unless otherwise made apparent in the context, the term“coupled” can be used to indicate that two or more elements are ineither direct or indirect (with other intervening elements between them)contact with each other, or that the two or more elements co-operate orinteract with each other (e.g., as in a cause and effect relationship),or both.

Passive Detection Configuration

FIG. 1 is a diagram of a passive detection environment 100 for receivingEMF signals to obtain bioelectrical signals, according to someembodiments. The environment 100 can perform passive detection using anEMF sensor system to obtain bioelectrical signals such as EEG and ECGsignals. The environment 100 includes a body 105 that emits EMF signals100. The EMF signals 100 can be detected by the passive detection system115. The passive detection system 115 includes an antenna 120 and anamplifier 125.

The antenna 120 can be a radio-frequency (RF) antenna or magnetic probeplaced close to the human body. The placement may be determined bydefined locations that maximize detection of EMF signals associated withvarious parts of the body, e.g., head, upper torso, and/or wrist. Thebody 105 emits EMF signals 110 that can be received by the antenna 120of a passive detection system 115.

The received signal is then passed to amplifier 125 where the gain ofthe received signal is increased for further signal processing. Forexample, the signal detected by antenna may be amplified by a low noiseamplifier (LNA). With proper frequency down-conversion, the signal canbe observed and recorded for analysis.

Active Detection Configuration

FIG. 2 is a diagram of an active detection environment 200, inaccordance with some embodiments. The active detection environment 200can utilize RF antennas to send custom or arbitrary RF waveforms andreceive EMF signals from the body. Arbitrary signal generation is usedto generate RF harmonic signals to propagate through the human body fromRF antennas. For example, arbitrary signal generation can generatedifferent waveforms from mathematical modeling along with differentamplitudes, bandwidths, and frequencies. The environment 200 includes ahuman 205, an active detection transmission module 210, and an activedetection reception module 235.

The active detection transmission module 210 may be used to reflect orexcite EMF signals from the human body when a wideband or narrowbandexternal transmission source is placed near the human body. For example,a very wideband transmission may include signals from DC to 10 KHz. Anarrowband transmission may be a single tone (e.g., 100 MHz). The activedetection transmission module 210 includes a signal generator 215,amplifier 220, and transmission antenna 225. The signal generator 215generates an EMF signal 230 near body 205. For example, the signalgenerator 215 is used to send a single tone (e.g., 100 MHz) signal to aVHF antenna.

The generated signal is amplified by amplifier 220 and transmitted usingantenna 225. In some embodiments, more than one antenna may be used totransmit RF signals. Additionally, the antennas may be placed around thehuman body. For example, antennas may be placed around the head, heart,chest, and abdomen. The custom magnetic and RF antennas are designed forhigh efficiency and compensate for body impedance at desired frequencybands.

The active detection reception module 235 receives the EMF signalstransmitted by the active detection transmission module 210 andreflected or excited by body 205. The active detection reception module235 includes antenna 240 and amplifier 245. The antenna 240 may be aradio-frequency (RF) antenna or magnetic probe placed close to the humanbody. The placement may be determined by defined locations that maximizedetection of EMF signals associated with various parts of the body. Thebody 205 reflects EMF signals 230 that are received by antenna 240 ofactive detection reception module 235.

The received signal is then passed to amplifier 245 where the gain ofthe received signal is increased for further signal processing. Forexample, the signal detected by antenna may be amplified by a low noiseamplifier (LNA). With proper frequency down-conversion, the signal canbe observed and recorded for analysis

Active detection using an active source enhances the weak signalsignature by using a carrier signal. The transmitted carrier signal hasstronger amplitude and a controlled frequency. In this setting, theintroduced embodiments may use a mixer such that the human body behaveslike a non-linear channel, which can generate harmonics signals when asingle tone signal passes through the human body channel. The signal maybe mixed with other environmental signals that enter the human body(e.g., WiFi, 4G, VHF, and/or other RF signals) or another designed testtone signal. The product of this mixing is called intermodulation (IMD)tones, which, in some cases, fall in different receive bands of thecommunication system.

The weak EMF signals coupled with stronger harmonic signals become newmodulation signals with detectable power levels seen by a receiver. Thenew modulation signals include high-order intermodulated signals,including the input tones, third-order products, and high-orderproducts. They have lower amplitudes from the carrier tones but stillhave a 20-dB dynamic range referring to the carrier signal amplitudelevel. The modulated EMF signal can be detected by the receiver and putinto the demodulation process by using signal processing algorithm.

Note, however, that an active detection configuration with transmittedcarrier signal may be less desirable, as compared to a passive detectionconfiguration, in an environment where unnecessary EMF emission shouldbe avoided (e.g., in a hostile, combative environment).

Hybrid Antenna System

Embodiments of the disclosed antenna system can detect EMF signals withdifferent frequency ranges. Additionally, the antenna can be designed ina loop, monopole, dipole, or wire antenna placed in a certain distancefrom the human body. In some embodiments, the antenna may be an array orgrid structure to scan the human body. In yet other embodiments, theantenna may be conformal or wearable structure embedded with textile.

The antenna system can be integrated into a body suit without inhibitingthe movement of the user. The bandwidth of probe antenna and RFcomponents are typically narrowband. Therefore, to detect and observethe whole spectrum of triggered or induced signals, very widebandcomponents are needed. For example, very wideband components can supportEMF signals from DC to 10 KHz. Contact based electrodes attach directlyto the body surface. However, to use a probe antenna integrated with atextile worn by the human body, there is a gap between the sensor andthe body. Therefore, non-contact antenna is provided to detect EMFsignals without degradation of bio-signals.

For purposes of the present disclosure, an EMF antenna system thatincludes at least a contact input source (e.g., an electrode) and anon-contact input source (e.g., an antenna) may be referred to herein asa “hybrid” antenna system.

FIG. 3 depicts a diagram of a hybrid antenna system 300 worn on the head305 of a user to monitor the EMF signals of the user.

Hybrid antenna system 300 may use the mechanisms of EMF generationlinked to the muscle electro-impulse response and energy conversationsfrom body electrochemistry effects. The hybrid antenna system 300 usesboth contact electrodes and non-contact antennas (i.e., a hybridapproach) to detect vital EMF signals. The non-contact antennas useactive circuits to detect signals at such low frequencies. Hybridantenna system 300 also detects common ground and reference signals,which are critical since they are the reference signals used to cancelthe commonly seen noise (e.g., powerline noise, such as 60 Hz).

The example antenna system 300 includes a ground contact 315, an earreference module 320, a contact electrode 325, non-contact antennas 330a and 330 b, and a Bluetooth™ module 335. The entire system may be wornover the head which may include hair 310, where contact electrodeplacement is not suitable.

The ground contact 315 provides a return path for the signals detectedby antenna system 300. The ear reference module 320 is a contact-basedelectrode for receiving EMF signals emitted from head 305. For example,ear reference module 320 uses traditional electrodes to connect to theskin to detect reference signals. The contact electrode 325 is also acontact-based electrode for receiving EMF signals emitted from head 305.For example, ear reference module 320 uses traditional electrodes toconnect to the skin to detect EEG/ECG signals.

Many of contact-based biomonitoring electrodes of ECG and EEG arecomprised of a plastic substrate covered with an Ag/AgCl compound. Theelectrode can be assembled with an electrolyte gel since the skininterface may contain an excess of chloride ions in solution such asperspiration. Such combination can be done by coating those compounds onthe plastic substrate (i.e., stud). The gel is also used on the skin ofpatients when checking their ECG. However, the gel may dry out or onlycan last a few hours or days after placed on the patient. The conductivecarbon fiber, or other conductive materials, should be qualified toreplace current compound and metal materials used in current electrodesor new probes. The probe-to-skin impedance and its dimension will bedecided by contact area, skin properties, and the materials used.

The electrode used in ECG detection can be a tiny patch which connectsto the patient. ECG electrodes are used for sensing bioelectricpotential, generally the electrical activity, caused by cardiac muscle.This electrical activity can be viewed as a small electric field or fluxof charge-carrying particles (i.e., current). The electrodes work astransducers converting this current flow from the body into the electronflow of the metallic wire. After amplified and processed, the ECG signalcan be observed. Very often a high ionic concentration gel is used inthe skin-electrode interface to increase conductivity due to smallsignal magnitude. The electrode may be a silver-silver chlorideelectrode.

In some embodiments, the electrode module includes a plastic substratecovered with an Ag/AgCl compound, an electrolyte gel coated on theplastic substrate to provide a high ionic concentration, and aconductive material to detect EMF signals when the electrode module isin contact with a human surface. In some embodiments, an electrodemodule includes two pre-gel (i.e., prior to gel being applied)electrodes placed on the head of a human body to detect the vital signsof the human body.

In some embodiments, the electrode may be placed in contact with the earto detect a reference signal. The ear is a suitable location to detectEMF signals from the body because it has relatively less noise. This isbecause the ear does not have any muscles and thus would not introduceEMF signals resulting from the muscle. However, other nodes can be usedas needed.

The non-contact antennas 330 a and 330 b detect EMF signals withoutrequiring direct contact to the human body. The non-contact antennas 330a and 330 b use low frequency antennas, from extreme low frequency (ELF)to very low frequency (VLF), to collect the bioelectrical signals suchas EEG/ECG signals. The antenna does not need to contact the skindirectly. Thus, the antenna performs EEG/ECG signal detection at adistance from the skin that is greater than the distance between acontact-based electrode and the skin. The antenna frequency is very low(10 Hz to 10 KHz) and thus its wavelength is long (e.g., the wavelengthof a 5 KHz signal is about 60,000 meters and the wavelength of a 10 Hzsignal is about 30,000,000 meters). Additionally, the minimum requiredelectrical wavelength for the traditional antenna is 0.1 wavelength toguarantee an efficient radiation efficiency.

The Bluetooth module 335 can be provided to transmit and receive datarelated to the signals detected by the ear reference module 320, contactelectrode 325, and non-contact antennas 330 a and 330 b. For example,the Bluetooth module 335 may transmit the detected signals to a signalprocessing module for signal processing, analysis, and data storage.

The various components of the antenna system 300 can be implemented in amanner that is consistent with the various embodiments described herein.

Antenna Signal Path

FIG. 4 depicts an antenna signal path 400 that includes antenna material405, an antenna matching circuits 410, and a receiver 415. The signalpath 400 represents the path of the EMF signal originating from amonitored body to an amplified for signal processing.

Antenna Material

Antenna material 405 includes a conductive material that receives EMFsignals from a monitored human body. In some embodiments, the antenna isan electro-textile based antenna including non-conductive, interlacingfibers 420 and conductive yarn 425. In some embodiments, the flexibleantenna patch is embedded in a flexible substrate. For example,non-conductive, interlacing fibers 420 may form a flexible antenna patchintegrated into clothing worn by the monitored human body. Theconductive yarn 425 may be wound around individual fibers of thenon-conductive interlacing fibers 420, such that the non-conductivefiber 425 and conductive fiber 425 form a textile patch for receivingEMF signals from a human body without contact with the human body.

Antenna material 405 may use a variety of elements or materials. In someembodiments, silver ink and copper wires are good conductors but theyare less suitable to be implemented on or be part of fabric forclothing. Conductive fiber materials (e.g., electro-textile) may be usedas conductive yarn so that the antenna radiator pattern can be builtwith the clothes in a weaving process. In some embodiments, the antennamaterial 405 may be a meshed antenna using conductive fiber was made bya very fine conductive silver thread (e.g., Agsis SilverAGSIS100D-1KAG).

Conductive thread is suitable since it can be used to modify existingclothing. Silver is ideal since silver oxide is highly conductivepossesses excellent RF properties. Additionally, the cost of silver issignificantly less than alternative conductive material such as gold.

Antenna material 405 may be used in a variety of shapes. For example, aplanar antenna can be integrated with a conformal patch that fits inexisting clothing. This conformal structure may cause additionalresonances which may be generally undesirable. However, this property isgood in this application because a wider bandwidth is desired. In someembodiments, to fit the property of the textile material, a meshedtexture antenna can be used to replace the conventional patch antennawith a solid surface. Additionally, antenna material 405 may useflexible PCB materials to fabricate the meshed antenna.

In some embodiments, the antenna material 405 may be formed as anon-uniform meshed path antenna. Non-uniform meshed patch antennas havesignificantly less conductor coverage than a conventional meshed patchantenna. Less conductor coverage reduces the usage of the specializedconductive fiber materials, which in turn can reduce the cost of theantenna material.

Active Antenna Circuits

The antenna system uses two ways to reduce the electrical wavelength.First, the antenna system changes the transmission line materials toincrease the effective electrical length. Second, the antenna systemconnects the shortened antenna with active antenna circuits. With theabove two factors, the physical length can be greatly reduced to use ashorter antenna length to receive the vital signal from the human body.Additionally, while the environment is changing, such as when the useris in motion, the antenna system may become detuned and mismatched tothe RF circuit front-end. The resulting signal loss may be significantin specific frequency ranges. Furthermore, when there is gap or othermedia between the body and the antenna, additional loss will result inlower signal to be received. To mitigate this impact, the active antennacircuits actively compensate for the changing conditions using thecomponents described below.

Antenna circuits 410 includes electronic circuits that can obtain thesignals received by antenna material 405 and process the signals so thatthey are suitable for further signal processing (e.g., at a subsequentstage, such as at the receiver module and/or the signal processingmodule). Antenna circuits 410 may include tunable module 411, filter412, and amplifier 413.

Tunable module 411 facilitates wideband tuning and signal amplification.and may be implemented with tunable capacitors. Wideband tuning mayfacilitate reception of signals at frequencies between and including theELF and VLF frequency bands. In some embodiments, the tunable capacitorsextend the bandwidth of the antenna to include the ELF frequency bandand the VLF frequency band. Filter 412 may be a band-pass orband-rejection filter that passes the input signal in most frequenciesbut filters signals in specific frequency bands. For example, filter 412may pass the detected EMF signal but attenuate one or more predeterminedfrequencies (or frequency range(s)) for background noise suppression.Commonly seen background EMF noise can include those signals in the 60Hz frequency band, which are typically introduced by the powerline powersupply. Amplifier 413 increases the power of the signal output of filter412. For example, amplifier 413 may amplify low frequency signals withfrequencies from 5 Hz-1 KHz.

Receiver

Receiver 415 can include impedance matching modules, differentialamplifiers, and filters for processing the received EMF signals from theantenna system. For example, the impedance matching module maximizes thepower transfer of the received signal by matching the source load of theantenna system.

The differential amplifier enhances the gain of the received signalbased upon the received reference signal. The non-contact signal andcontact signal enter the instrument amplifier such as differentialamplifiers. Since the amplitude from the non-contact node is amplifiedto a similar level of the contact node (e.g., the reference signal), thenoise and interference cancellation can be performed inside thedifferential amplifier circuits. The filters reduce noise such aspowerline noise (e.g., noise at 60 Hz).

The various components of the antenna signal patch 400 can beimplemented in a manner that is consistent with the various embodimentsdescribed herein.

Antenna Circuit Embodiment

FIG. 5 depicts a circuit diagram of antenna circuit 500 consistent withvarious embodiments disclosed herein. The active antenna circuit 500includes various circuit components that may be adjusted to performantenna matching, wideband tuning, and signal amplification. Antennacircuit 500 shown in FIG. 5 may be an embodiment of circuit 410described above. For example, tuning circuit 510 is an embodiment oftuning circuit 411, filter circuit 520 is an embodiment of filter 412,and voltage amplifier 530 and emitter-follower amplifier 540 is anembodiment of amplifier 413. An active antenna circuit is distinguishedfrom a passive antenna because the circuits utilize an external powersource (e.g. DC power source 804) to power an amplifier. Additionally,the antenna circuit 500 may use bipolar junction transistors (BJT)transistors with lump elements to perform the antenna matching.

Since the body signal typically has a weak signal strength, the receivedsignal must be amplified and filtered before the signal processing canbe applied. The RF path is the first opportunity to moderate the lossand noise. For example, a high efficiency antenna and differentialamplifiers may be used to maintain gain, reduce noise, and increase thechance to detect weak bioelectrical signals.

Instead of using discrete components, the antenna tuner can be a highlyintegrated module consisted of several switches and tunable capacitorsfor more flexible tuning. The bipolar junction transistor (BJT) or fieldemitter transistor (FET) based active circuit is used to enhance thegain and filtering. Additionally, the bandwidth of the antenna isextended while minimizing the reduction in antenna efficiency.

The various components of active antenna circuit 500 can be implementedin a manner that is consistent with the various embodiments describedherein.

EMF Signal Path

FIG. 6 depicts a block diagram of an EMF signal path 600 consistent withvarious embodiments disclosed herein. EMF signal path 600 is a signalpath starting from the EMF signals 610 emitted from human body 605. Thesignals are detected by an antenna module 615, a reference signal module630, and a contact signal module 635. The detected signals then proceedalong the EMF signal path 600 to a receiver 640 and a signal processingmodule 650.

Antenna signal module 615 includes an antenna 620 and an antenna circuitmodule 625. According to one or more embodiments, the antenna 620detects a non-contact EMF signal, and the antenna circuit module 625performs wideband tuning and amplifies the non-contact EMF signal. Forexample, wideband tuning may facilitate reception of signals atfrequencies between and including the ELF and VLF frequency bands.

Reference signal module 630 includes an electrode to detect a referencesignal from the human body 605. For example, the electrode may be acontact-based electrode that is placed on the ear of the human body 605.The contact signal module 635 includes an electrode to detect an EMFsignal from the human body 605. For example, the electrode may be acontact-based electrode placed on various parts of the human body 635 todetect localized EMF signals.

Receiver module 640, in some implementations, includes an impedancematching module 645 and differential amplifier 650. Impedance matchingmodule 645 improves the power transfer of the EMF signals by matchingthe source impedance of the antenna module. Differential amplifier 650generates bioelectrical signals including a contact bioelectrical signalby amplifying the contact EMF signal and a non-contact EMF signals

Signal processing module 650, in some implementations, includesprocessor 665 and storage 670. Processor 665 applies a filteringalgorithm to improve the signal-to-noise ratio of the bioelectrical EMFsignals and to perform digital signal processing on the bioelectricalEMF signals. Storage 670 provides data storage to maintain dataregarding the detected EMF signals. The stored data may be used toperform further signal processing in the future. For example, signalsmay be stored until enough signal data is gathered to perform comparisonor correlation related analysis.

The various components of the EMF signal path 600 can be implemented ina manner that is consistent with the various embodiments describedherein.

EMF Detection System

FIG. 7 depicts a block diagram of an EMF detection system 700 consistentwith various embodiments disclosed herein. EMF detection system 700includes an electrode 701, an electrode 702, an active antenna module705, a receiver 710, and a signal processing module 720.

Electrode 701 may include a contact-based electrode to detect areference signal 730 from a human body. In some embodiments, theelectrode may be a contact-based electrode that is placed on the ear ofthe human body. The ear is a suitable contact point for the electrodebecause it does not contain muscle tissue which emits EMF signals. Thus,the detected signal includes the desired EMF signals indicating thephysical condition of the monitored body and contains less noise thatinterferes with the desired signal. In other embodiments, electrode 701may be placed on the neck or other locations that allow direct contactwith the skin of the body. Electrode 701 outputs contact referencesignal 730, which is based on the detected reference signal. Forexample, electrode 701 outputs reference signal 730 to receiver 710 toprepare the signal for signal processing.

Electrode 702 may include an electrode to detect an EMF signal from ahuman body. For example, the electrode may be a contact-based electrodethat is placed on the head of the human body to measure EEG signals. Thecontact-based electrode is placed in direct contact with skin in orderto detect the EEG signals such as on the forehead or neck. The placementof the contact-based electrode should avoid hair because hair does notconduct current and thus does not transmit EMF signals. More than onecontact-based electrode may be placed on the head to collect more thanone EMF signals from the human body. For example, the contact-basedelectrode may be placed on various parts of the head to detect localizedEEG signals. This is important because EEG activity in different partsof the brain may indicate distinguishable physical conditions or brainactivities. Electrode 702 outputs contact EMF signal 731. For example,electrode 702 outputs contact signal 731 to receiver 710 to prepare thesignal for signal processing.

Active antenna module 704 includes direct current (DC) power source 705,antenna trace and material 706, tunable module 707, band-stop filter708, and ELF-VLF Amplifier 709. DC power source 705 provides power tooperate the antenna circuits (e.g., tunable module 707, band-stop filter708, and ELF-VLF Amplifier 709).

Antenna trace and material 706 facilitates the detection of non-contactbased EMF signals. In some embodiments, antenna trace and material 706includes a conductive material that receives EMF signals received from amonitored human body. For example, the antenna may an electro-textilebased antenna forms a flexible antenna patch. In some embodiments, theconductive yarn may be wound around individual fibers of thenon-conductive interlacing fibers, such that the non-conductive fiberand conductive fiber form a textile patch for receiving EMF signals froma human body without contact with the human body. The various componentsof the antenna signal patch 400 can be implemented in a manner that isconsistent with the various embodiments described herein, such as thosedescribed at FIG. 4.

Tunable module 707 facilitates wideband tuning and signal amplification.Tunable module 707 includes tunable capacitors. In some embodiments, thetunable capacitors extend the bandwidth of the antenna to include theELF frequency band and the VLF frequency band. Band-stop filter 708passes the signal in most frequencies unaltered but filters signals inspecific frequency bands. A band-stop filter may also be aband-rejection filter. For example, band-stop filter 708 may pass thedetected EMF signal from antenna trace and material 706 but attenuatesthe signal in the 60 Hz frequency band. This reduces the noiseintroduced by the powerline power supply (e.g., DC power source 705).ELF-VLF amplifier 709 increases the power of the signal output ofband-stop filter 708. For example, ELF-VLF amplifier 709 may amplify lowfrequency signals with frequencies from 5 Hz-1 KHz. As described above,ELF is defined by the ITU as electromagnetic radio waves withfrequencies from 3 to 30 Hz. VLF is defined by the ITU aselectromagnetic radio waves with frequencies from 3 kHz to 30 kHz. Thus,ELF-VLF amplifier 709 may amplify frequencies from 5 Hz-1 KHz in orderto amplify all signals between the ELF and VLF frequency bands. Alsonoted above, ELF-VLF amplifier 709 is powered by DC power source 705.

After passing the non-contact EMF signal through antenna trace andmaterial 706, tunable module 707, band-stop filter 708, and ELF-VLFAmplifier 709, the active antenna module 704 outputs non-contact EMFsignal 732 to receiver 710 to prepare the signal for signal processing.

Receiver 710 processes the detected EMF signals to prepare the signalsfor signal processing. To achieve this, receiver 710 includes antennamatching module 711, band-stop filter 712, band-stop filter 713,differential amplifier 714, low noise amplifier 715, bandpass filter716, analog-to-digital converter (ADC) 717 and transceiver 718.

Antenna matching module 711 ensures adequate power transfer from activeantenna module 704. This is accomplished by matching the source load ofthe antenna module. In some embodiments, antenna matching moduleincludes a resistor, inductor, and capacitor connected in series tocreate a resistor-inductor-capacitor (RLC) circuit network that is tunedto match the source load of the antenna module.

Band-stop filter 712 takes the output of antenna matching circuit 711corresponding to contact EMF signal 731 or non-contact EMF signal 732.Similarly, band-stop filter 713 takes the output of antenna matchingcircuit 711 corresponding to contact reference signal 730. For example,band-stop filter 712 and band-stop filter 713 may attenuate the signalin the 60 Hz frequency band to perform powerline noise rejection.

Differential amplifier 714 is an amplifier that amplifies the differencebetween two input voltages and attenuates the voltage common to the twoinputs. In some embodiments, differential amplifier 714 amplifies thedifference between the reference signal and non-contact EMF signal toproduce a non-contact bioelectrical signal and amplify the differencebetween the reference signal and contact EMF signal to produce a contactbioelectrical signal. In other words, a non-contact bioelectrical signalis produced by using differential amplifier 714 to amplify thedifference between the non-contact EMF signal and the reference signal.Similarly, contact bioelectrical signal is produced by usingdifferential amplifier 714 to amplify the difference between the contactEMF signal and the reference signal. Although differential amplifier 714is depicted as a signal amplifier, differential amplifier 714 may beimplemented as multiple amplifiers. Each amplifier takes as input thereference signal and a detected EMF signal. As such, bioelectricalsignals are generated by amplifying the difference between a detectedEMF signal and the reference signal.

Low noise amplifier 715 amplifies a low-power signal without degradingthe signal-to-noise (SNR) of the signal. In some embodiments, low noiseamplifier 715 amplifies the output of differential amplifier 714. Theamplified signal output is provided as input into bandpass filter 716.Band-pass filter 716 passes frequencies within a certain range butattenuates the signal outside of the range. In some embodiments,bandpass filter 716 passes frequencies between 5 Hz-10 KHz. This rangeallows signals from the ELF frequency band to the VLF frequency band topass through. The signal passed from bandpass filter 716 is provided asinput into analog-to-digital converter 717. The analog-to-digitalconverter 717 converts the detected EMF signals into a digital signalfor digital signal processing at signal processing module 720. Thedigital signal output by analog-to-digital converter 717 is provided totransceiver 718 for transmission as data transmission signal 733 tosignal processing module 720. In some embodiments, transceiver 718 maytransmit data transmission signal 733 to signal processing module 720via wireless transmissions. For example, transceiver 718 may be aBluetooth enabled module that transmits data transmission signal 733 tosignal processor 720 via Bluetooth. In other embodiments, transceiver718 may transmit data transmission signal 733 to signal processingmodule 720 using a wired transmission.

Signal processing module 720 may include transceiver 721, detectionmodule 722, tracking module 723, processor 724, and storage module 725.Depending on the implementation, one or more modules can be added orremoved to suit the purpose of a specific field application. Signalprocessing module 720 receives data transmission signal 733 fromreceiver 710. Signal processing module 720 applies digital signalprocessing, signal analysis, and data storage on received datatransmission 733. Signal processing includes preliminary EMF detectionand processing. Multiple measurements are performed with a variety ofsampling rates and signal durations. Each measurement is analyzed usinghuman EMF decomposition algorithm. In some frequency bands, the signalsmeasured with or without a monitored human body show repeatabledifferences.

First, transceiver 721 facilitates the reception of data transmission733. Data transmission 733 includes the digital signals produced byreceiver 710. In particular, data transmission signal 733 may includecontact and non-contact bioelectrical signals based on the contactreference signal 730, contact EMF signal 731, and non-contact EMF signal732. Once data transmission signal 733 is received, transceiver 721provides the data for processing and storage by detection module 722,tracking module 723, processor 724, and storage module 725.

Detection module 722 detects characteristics of the bioelectricalsignals to identify physical conditions of the monitored body thatcorrespond to the detected bioelectrical signals. For example, detectionmodule 722 may perform peak detection, sampling rate control, and/ordigital filtering on the amplified bioelectrical signals.

Additionally, detection module 722 searches the EEG signal patterns withthe extreme conditions. For example, besides observing the traditionalEEG spectrum from DC to 100 Hz, detection module 722 scans widebandspectrums up to several kHz. This design can cover the spectral rangefrom DC to 10 kHz with 10000 (40 dB) voltage gain.

Tracking module 723 tracks changes in the bioelectrical signals. Inparticular, tracking module 723 tracks and associates signaturesextracted from active and passive systems. In other words, trackingmodule 723 performs a correlation function on the bioelectrical signalswith known bioelectrical signal sets to exclude uncertainty in thebioelectrical signals. The types of received signals are mostlynon-stationary and instantaneous with non-periodic features. Since mostsignal processing algorithms are designed for stationary and periodicwaveforms with at least some identifiable features, knowledge of thewaveforms must first be acquired in order to apply the algorithms tonon-stationary, non-periodic waveforms. After acquiring knowledge of thesignal properties and being able to estimate the signal resolution intime or frequency domain in advance, the system is able to capture thesignal. In some embodiments, tracking module 723 applies weighteddecisions and loop detection to enhance the detection of bioelectricalsignals corresponding to known bioelectrical signals. Additionally,tracking module 723 may apply machine learning and feedback todynamically enhance the detection of known bioelectrical signals.

As described above, most of the EMF signals from the human body fallbetween two extremes (i.e., between ELF and VLF). Additionally, the EMFsignals are generally non-stationary and non-periodic. To make data fromthe signal useful and reliable, the detected EMF signals may be trackedwith tracking algorithms. Here the specially designed tracking filter isapplied, which can be designed for multiple target tracking to associatethe relevant EMF data in same track. It can be easier to track andupdate tracking along time, analyze the signal signature, and track thedifferences.

In some embodiments, tracking module 723 performs correlation functionon the EMF signals with known EMF signals to exclude uncertainty in thebioelectrical signals. Correlation functions measures the similarity oftwo signals as a function of the displacement of one signal relative toanother. For example, correlation may be performed suing a sliding dotproduct or sliding inner-product calculation. In some embodiments, thetracking module uses intermodulation techniques. The intermodulationtechniques are applied by performing measurements at the range offrequencies of the signals to be detected and up the 7th order ofharmonics of the signals to be detected.

Processor 724 analyzes the characteristics and changes of thebioelectrical signals. For example, processor 724 analyzes the EMFsignals to detect EMF signals corresponding to physical conditions suchas injury, health status, and physical activities.

Processor 724 performs human EMF mode decomposition to decompose asignal into intrinsic mode functions (IMF) along with a trend, andobtain instantaneous frequency data. It is designed to work well fordata that is nonstationary and nonlinear. Empirical mode decomposition(EMD) may be used to decompose the signal into different IMFs. The IMFswhich may contain possible EMF modulations can be selected into nextstage for post signal processing.

Processor 724 performs signal enhancements. One effective way to enhancethe signal is to apply a matched filter. A matched filter is a signalprocessing technique used to increase the signal to noise ratio (SNR).Usually a perfectly matched filter can increase the signal level by 50dB. To get ideal signal enhancement, a long sequence waveform is storedin correlation memory. In some embodiments, the long sequence waveformmay be stored in data storage module 725.

To characterize the EEG signals, processor 724 uses an 8 dB waveletfunction to decompose the EEG signals into bandwidths known as alpha,beta, theta, delta, and gamma waves. The decomposed signals and FFTspectra may be analyzed. For example, the alpha wave, which canassociate with eye closing, has a larger amplitude when the monitoredbody performs an eye blink compared to when the monitored body is in arelaxed state without performing an eye blink. In some embodiments,processor 724 applies a filtering algorithm to remove noise in atime-frequency domain to perform spectrogram digital signal processingon the bioelectrical signals. Processor 724 may also apply a filteringalgorithm in a time domain and frequency domain to perform time domainand frequency domain digital signal processing on the bioelectricalsignals.

The various components of the EMF detection system 700 can beimplemented in a manner that is consistent with the various embodimentsdescribed herein.

FIG. 8 depicts a block diagram of an EMF detection system 800 consistentwith various embodiments disclosed herein. Many of components disclosedin EMF detection system 800 are consistent with the components disclosedin EMF detection system 700. In addition to components common to bothsystems, EMF detection system 800 also includes additional harmonicsignal processing module 830. Harmonic signal processing is based on theconcept that a signal is composed of a sum of oscillatory components.

The output of differential amplifier 814 is input into two-way splitter815. Two-way splitter 815 then outputs the input to both signalprocessing module 820 and harmonic signal processing module 830.Harmonic signal processing 830 receives a signal to perform harmonicsignal processing.

Harmonic signal processing 830 includes a LO signal source 831, mixer832, band pass filter 833, and ADC 834. LO signal source 831 comprises alocal oscillator that is used with mixer 832 to change the frequency ofa signal. The local oscillator may be a crystal oscillator that providesstability and high performance for a fixed frequency. Alternatively, theoscillator may be a variable-frequency oscillator to provide signals atdifferent frequencies. Together, the LO signal source 831 and mixer 832functions as a converter that converts the frequency of the signalreceived from two-way splitter 815. The converted signal is then sentthrough band-pass filter 833 and ADC 834.

Band pass filters passes frequencies within a certain range butattenuates the signal outside of the range. In some embodiments,bandpass filter 833 passes frequencies between 0.8-10 KHz. The signalpassed from bandpass filter 833 is provided as input intoanalog-to-digital converter 834. The analog-to-digital converter 834converts the EMF signals into a digital signal for digital signalprocessing (DSP) at signal processing module 840.

Using the harmonic signal processing module 830, harmonic testingharmonic testing may be performed using: (1) signal tone sine wave, (2)frequency modulated continuous-wave (FMCW) signal with a 3-kHzbandwidth, (3) noise with a 3-kHz bandwidth, and (4) an up-converted ECGsignal. Each waveform can be mixed with a 10-kHz LO signal by mixer 832.The time domain, frequency domain and the 3rd harmonics for eachscenario are examined to find the signature of ECG waveform after mixingwith the designated LO signal. Based upon harmonic testing, it isdetermined that the 3rd harmonic spectral signature of the up-convertedECG signal is like a single-tone waveform.

Harmonic signal processing can be performed in order to understand andcalibrate the intermodulation from the mixer, cables, signal generators,and digitizer of the system. In one or more examples, a two-tonemeasurement around the frequency range of the interested signals and upto the 7th order of its harmonics is performed.

The various components of the EMF detection system 800 can beimplemented in a manner that is consistent with the various embodimentsdescribed herein.

FIG. 9 is a high-level block diagram illustrating an example of aprocessing system in which at least some operations described herein canbe implemented (e.g., signal processing modules 660, 720, 840),consistent with various embodiments. The processing system can beprocessing device 900, which represents a system that can run any of themethods/algorithms described above. A system may include two or moreprocessing devices such as represented in FIG. 9, which may be coupledto each other via a network or multiple networks. A network can bereferred to as a communication network.

In the illustrated embodiment, the processing device 900 includes one ormore processors 910, memory 911, a communication device 912, and one ormore input/data (I/O) devices 913, all coupled to each other through aninterconnect 914. The interconnect 914 may be or include one or moreconductive traces, buses, point-to-point connections, controllers,adapters and/or other conventional connection devices. Each of theprocessors 910 may be or include, for example, one or moregeneral-purpose programmable microprocessors or microprocessor cores,microcontrollers, application specific integrated circuits (ASICs),programmable gate arrays, or the like, or a combination of such devices.The processor(s) 910 control the overall operation of the processingdevice 900. Memory 911 may be or include one or more physical storagedevices, which may be in the form of random access memory (RAM),read-only memory (ROM) (which may be erasable and programmable), flashmemory, miniature hard disk drive, or other suitable type of storagedevice, or a combination of such devices. Memory 911 may store data andinstructions that configure the processor(s) 910 to execute operationsin accordance with the techniques described above. The communicationdevice 912 may be or include, for example, an Ethernet adapter, cablemodem, Wi-Fi adapter, cellular transceiver, Bluetooth transceiver, orthe like, or a combination thereof. Depending on the specific nature andpurpose of the processing device 900, the I/O devices 913 can includedevices such as a display (which may be a touch screen display), audiospeaker, keyboard, mouse or other pointing device, microphone, camera,etc.

While processes or blocks are presented in a given order, alternativeembodiments may perform routines having steps, or employ systems havingblocks, in a different order, and some processes or blocks may bedeleted, moved, added, subdivided, combined, and/or modified to providealternative or sub-combinations, or may be replicated (e.g., performedmultiple times). Each of these processes or blocks may be implemented ina variety of different ways. In addition, while processes or blocks areat times shown as being performed in series, these processes or blocksmay instead be performed in parallel, or may be performed at differenttimes. When a process or step is “based on” a value or a computation,the process or step should be interpreted as based at least on thatvalue or that computation.

Software or firmware to implement the techniques introduced here may bestored on a machine-readable storage medium and may be executed by oneor more general-purpose or special-purpose programmable microprocessors.A “machine-readable medium”, as the term is used herein, includes anymechanism that can store information in a form accessible by a machine(a machine may be, for example, a computer, network device, cellularphone, personal digital assistant (PDA), manufacturing tool, any devicewith one or more processors, etc.). For example, a machine-accessiblemedium includes recordable/non-recordable media (e.g., read-only memory(ROM), random access memory (RAM), magnetic disk storage media, opticalstorage media, flash memory devices, etc.).

FIG. 10 is an active detection environment 1000 in accordance with oneor more embodiments of the present disclosure. Active detectionenvironment 1000 includes a signal generator 1010, a monitored subject1020, and a receiver 1030.

Signal generator 1010 includes a signal source 1011 to produce a sourcesignal, background noise signal, and/or interference signal. Thegenerated signal is then provided to antenna 1012 for transmission aspropagated signal 1012 through monitored subject 1020. Monitored body1020 can be treated as a communication channel. The antenna system 1030includes an electrode/antenna interface 1021, amplifier 1032, and filter1033. Electrode/antenna interface 1021 performs electrode/antennamatching on the electrodes and/or antennas (not shown) that detects thesignals propagated across monitor subject 1020. Amplifier 1032 andfilter 1033 modifies the received signal such that it is suitable forsignal processing. The various components of active detectionenvironment 1000 can be implemented in a manner that is consistent withthe various embodiments described herein.

FIG. 11 depicts a chart of contact points where electrodes may be placedfor performing contact-based EMF detection in accordance with one ormore embodiments of the present disclosure. The chart shows a side-viewrepresentation of a head 1100. Contact points include the nasion 1110,preaurical point 1120, mastoid process 1130, and inion 1140. Electrodesmay be used at one or more of the contact points to detect EMF andreference signals. The placement of multiple electrodes allows detectionof localized EMF signals around the brain. Additionally, each contactpoint has different characteristics that provide different signalcharacteristics. For example, placement of electrodes on the earproduces less noise because there is less muscle current at that contactpoint. The various components disclosed in FIG. 11 can be implemented ina manner that is consistent with the various embodiments describedherein.

CONCLUSION

From the foregoing, it will be appreciated that specific embodiments ofthe technology have been described herein for purposes of illustration,but that various modifications can be made without deviating from thetechnology. In representative embodiments, the EMF detection system canhave configurations other than those specifically shown and describedherein, including other circuit designs. The various modules andcircuits described herein may have other configurations in otherembodiments, which also produce the desired characteristics describedherein.

Certain aspects of the technology described in the context of particularembodiments may be combined or eliminated in other embodiments. Further,while advantages associated with certain embodiments of the technologyhave been described in the context of those embodiments, otherembodiments may also exhibit such advantages, and not all embodimentsneed necessarily exhibit such advantages to fall with within the scopeof the present disclosure. Accordingly, the present disclosure andassociated technology can encompass other embodiments not expresslyshown or described herein. For example, while processes or blocks arepresented in a given order, alternative embodiments may perform routineshaving steps, or employ systems having blocks, in a different order, andsome processes or blocks may be deleted, moved, added, subdivided,combined, and/or modified to provide alternative or sub combinations.Each of these processes or blocks may be implemented in a variety ofdifferent ways. Also, while processes or blocks are at times shown asbeing performed in series, these processes or blocks may instead beperformed in parallel, or may be performed at different times. Further,any specific numbers noted herein are only examples: alternativeimplementations may employ differing values or ranges.

To the extent any materials incorporated herein conflict with thepresent disclosure, the present disclosure controls.

We claim:
 1. A system for detecting bioelectrical signal, the systemcomprising: a reference module having a first electrode to detect areference electrical signal; a contact module having a second electrodeto detect a contact electrical signal; an antenna module, the antennamodule including (1) an antenna to detect a non-contact EMF signal, and(2) an antenna circuit module to perform wideband tuning and amplify thenon-contact EMF signal; a receiver module, the receiver module including(1) an impedance matching module to match a source impedance of theantenna module, the reference module, and the contact module; and (2) adifferential amplifier to amplify the difference between the referencesignal and the non-contact EMF signal to produce a non-contactbioelectrical signal, and to amplify the difference between thereference signal and contact signal to produce a contact bioelectricalsignal; and a signal processing module including a processor (1) toapply a filtering algorithm to increase the signal-to-noise ratio of thebioelectrical signals, including the non-contact and contactbioelectrical signals, and (2) to perform digital signal processing onthe bioelectrical signals.
 2. The system of claim 1, wherein the antennais an electro-textile based antenna including (1) non-conductive fibers,and (2) conductive fibers wound around individual non-conductive fibers,such that the non-conductive fiber and conductive fiber form a textilepatch for receiving EMF signals from a human body without contact withthe human body.
 3. The system of claim 2, wherein the antenna is aconformal patch that is embedded in clothing material.
 4. The system ofclaim 1, wherein the antenna is configured to receive signals from theextremely low frequency (ELF) band to the very low frequency (VLF) bandto detect electroencephalography (EEG) signals and electrocardiography(ECG) signals.
 5. The system of claim 1, wherein the antenna is one ofdipole, monopole, or loop antenna.
 6. The system of claim 1, wherein theantenna is a meshed patch antenna embedded in a flexible substrate. 7.The system of claim 1, wherein the antenna module includes a directcurrent (DC) power source to power the antenna circuit.
 8. The system ofclaim 1, wherein the antenna circuit module includes (1) a tunablemodule including a tunable capacitor, (2) a band-stop filter to reject apredetermined frequency of noise, and (3) an amplifier to amplify thenon-contact EMF signals.
 9. The system of claim 8, wherein the tunablecapacitor is operable to adjust the bandwidth of the antenna to includethe extremely low frequency (ELF) band and the very low frequency (VLF)band.
 10. The system of claim 1, wherein the impedance matching moduleincludes an RLC circuit network that is tuned to match the source loadof the antenna module.
 11. The system of claim 1, wherein the receivermodule includes a band-stop filter to reduce or suppress a predeterminednoise frequency from the non-contact EMF signals.
 12. The system ofclaim 1, wherein the receiver module includes a transceiver to transmitthe contact bioelectrical signal and non-contact bioelectrical signalsto the signal processing module.
 13. The system of claim 1, wherein thesignal processing module analyzes data related to the bioelectricalsignals, the signal processing module including (1) a detection moduleto detect characteristics of the bioelectrical signals, (2) a trackingmodule to track the changes to the bioelectrical signals, and (3) aprocessor for analyzing the characteristics and changes of thebioelectrical signals.
 14. The system of claim 13, wherein the detectionmodule performs peak detection, sampling rate control, and/or digitalfiltering on the bioelectrical signals.
 15. The system of claim 13,wherein the tracking module performs a correlation function on EMFsignals with known EMF signals to exclude uncertainty in thebioelectrical signals.
 16. The system of claim 13, wherein the trackingmodule applies weighted decisions and loop detection to enhancedetection of bioelectrical signals corresponding to known bioelectricalsignals.
 17. The system of claim 13, wherein the processor appliesmachine learning and feedback to dynamically enhance the detection ofknown bioelectrical signals.
 18. The system of claim 13, wherein theprocessor analyzes EMF signals to detect EMF signals corresponding tophysical conditions indicative of injury, health status, and/or physicalactivities.
 19. The system of claim 13, wherein the processor applies afiltering algorithm to remove noise in a time-frequency domain, andperforms spectrogram digital signal processing on the bioelectricalsignals.
 20. The system of claim 13, wherein the processor applies afiltering algorithm in a time domain and frequency domain, and performstime domain and frequency domain digital signal processing on thebioelectrical signals.
 21. The system of claim 13, wherein the processorapplies a matched filter to improve the signal-to-noise ratio of thebioelectrical signals.
 22. The system of claim 13, wherein the processorapplies a matched filter by sampling a bioelectrical signal measuredfrom the human body to produce a known bioelectrical signal used toperform a correlation function.
 23. The system of claim 13, wherein theprocessor decomposes EEG signals extracted from the bioelectricalsignals into alpha, beta, theta, delta, and/or gamma signals.
 24. Thesystem of claim 23, wherein the processor decomposes the EEG signalsusing an 8 dB wavelet function.
 25. The system of claim 13, wherein theprocessor applies intermodulation techniques to the bioelectricalsignals, the intermodulation technique applied by performingmeasurements at the range of frequencies of the signals to be detectedand up a predetermined order of harmonics of the signals to be detected.26. The system of claim 1, wherein an electrode includes (1) a plasticsubstrate covered with an Ag/AgCl compound, (2) an electrolyte gelcoated on the plastic substrate to provide a high ionic concentration,and (3) a conductive material to detect EMF signals when the electrodeis in contact with a human surface.